Search

Aim: Macroinvertebrates comprise a highly diverse set of taxa with great potential as indicators of soil quality. Communities were sampled at 3,694 sites distributed world-wide. We aimed to analyse the patterns of abundance, composition and network characteristics and their relationships to latitude, mean annual temperature and rainfall, land cover, soil texture and agricultural practices. Location: Sites are distributed in 41 countries, ranging from 55° S to 57° N latitude, from 0 to 4,000 m in elevation, with annual rainfall ranging from 500 to >3,000 mm and mean temperatures of 5–32°C. Time period: 1980–2018. Major taxa studied: All soil macroinvertebrates: Haplotaxida; Coleoptera; Formicidae; Arachnida; Chilopoda; Diplopoda; Diptera; Isoptera; Isopoda; Homoptera; Hemiptera; Gastropoda; Blattaria; Orthoptera; Lepidoptera; Dermaptera; and “others”. Methods: Standard ISO 23611-5 sampling protocol was applied at all sites. Data treatment used a set of multivariate analyses, principal components analysis (PCA) on macrofauna data transformed by Hellinger’s method, multiple correspondence analysis for environmental data (latitude, elevation, temperature and average annual rainfall, type of vegetation cover) transformed into discrete classes, coinertia analysis to compare these two data sets, and bias-corrected and accelerated bootstrap tests to evaluate the part of the variance of the macrofauna data attributable to each of the environmental factors. Network analysis was performed. Each pairwise association of taxonomic units was tested against a null model considering local and regional scales, in order to avoid spurious correlations. Results: Communities were separated into five clusters reflecting their densities and taxonomic richness. They were significantly influenced by climatic conditions, soil texture and vegetation cover. Abundance and diversity, highest in tropical forests (1,895 ± 234 individuals/m2) and savannahs (1,796 ± 72 individuals/m2), progressively

[Aim] Macroinvertebrates comprise a highly diverse set of taxa with great potential as indicators of soil quality. Communities were sampled at 3,694 sites distributed world-wide. We aimed to analyse the patterns of abundance, composition and network characteristics and their relationships to latitude, mean annual temperature and rainfall, land cover, soil texture and agricultural practices., [Location] Sites are distributed in 41 countries, ranging from 55° S to 57° N latitude, from 0 to 4,000 m in elevation, with annual rainfall ranging from 500 to >3,000 mm and mean temperatures of 5–32°C., [Time period] 1980–2018., [Major taxa studied] All soil macroinvertebrates: Haplotaxida; Coleoptera; Formicidae; Arachnida; Chilopoda; Diplopoda; Diptera; Isoptera; Isopoda; Homoptera; Hemiptera; Gastropoda; Blattaria; Orthoptera; Lepidoptera; Dermaptera; and “others”., [Methods] Standard ISO 23611-5 sampling protocol was applied at all sites. Data treatment used a set of multivariate analyses, principal components analysis (PCA) on macrofauna data transformed by Hellinger’s method, multiple correspondence analysis for environmental data (latitude, elevation, temperature and average annual rainfall, type of vegetation cover) transformed into discrete classes, coinertia analysis to compare these two data sets, and bias-corrected and accelerated bootstrap tests to evaluate the part of the variance of the macrofauna data attributable to each of the environmental factors. Network analysis was performed. Each pairwise association of taxonomic units was tested against a null model considering local and regional scales, in order to avoid spurious correlations., [Results] Communities were separated into five clusters reflecting their densities and taxonomic richness. They were significantly influenced by climatic conditions, soil texture and vegetation cover. Abundance and diversity, highest in tropical forests (1,895 ± 234 individuals/m2) and savannahs (1,796 ± 72 individuals/m2), progressively decreased in tropical cropping systems (tree-associated crops, 1,358 ± 120 individuals/m2; pastures, 1,178 ± 154 individuals/m2; and annual crops, 867 ± 62 individuals/m2), temperate grasslands (529 ± 60 individuals/m2), forests (232 ± 20 individuals/m2) and annual crops (231 ± 24 individuals/m2) and temperate dry forests and shrubs (195 ± 11 individuals/m2). Agricultural management decreased overall abundance by ≤54% in tropical areas and 64% in temperate areas. Connectivity varied with taxa, with dominant positive connections in litter transformers and negative connections with ecosystem engineers and Arachnida. Connectivity and modularity were higher in communities with low abundance and taxonomic richness., [Main conclusions] Soil macroinvertebrate communities respond to climatic, soil and land-cover conditions. All taxa, except termites, are found everywhere, and communities from the five clusters cover a wide range of geographical and environmental conditions. Agricultural practices significantly decrease abundance, although the presence of tree components alleviates this effect.

The municipality of Teresópolis, in the Rio de Janeiro mountain region, stands out in the production of vegetables, has all its agricultural activity in mountain environments, where the great intensity of crops causes disturbing environmental problems. The technologies based on agroecology propose actions that can improve the performance of agriculture in these environments. However, to support these actions, there is a need to study and better understand the productive dynamics in these environments. The objective of this work is to analyze the performance of agroecological production units (PUs), using the Data Envelopment Analysis (DEA) methodology, for a case study. The variables of cultivated area, external inputs, machine hours and man days as inputs were used; invoicing and different items produced, as outputs of the DEA model applied. The UP that presented the best performance, produced 34 different items, was efficient during nine months, with an efficiency index of 96%, in the year 2017. The combination or sequence between the types of crops, size of the areas destined to each one and times of planting constitute a productive dynamic capable of promoting the efficiency of each UP. The identification of efficient units and the understanding of the dynamics and the good productive practices, can help the farmers with less efficiency, in the improvement of the performance., O município de Teresópolis, na Região Serrana Fluminense se destaca na produção de hortaliças e tem toda a sua atividade agrícola em ambientes de montanha, onde a grande intensidade de cultivos provoca problemas ambientais preocupantes. As tecnologias de base agroecológica propõem ações que podem melhorar o desempenho da agricultura nesses ambientes. No entanto, para respaldar essas ações, existe necessidade de se estudar e compreender melhor a dinâmica produtiva, nesses ambientes. Este trabalho tem como objetivo analisar o desempenho de unidades produtivas (UPs) agroecológicas, usando a metodologia de análise envoltória de dados (DEA), para um estudo de caso. Foram utilizadas as variáveis de área cultivada, insumos externos, horas máquina e dias homem como inputs; faturamento e itens diferentes produzidos, como outputs do modelo DEA aplicado. A UP que apresentou o melhor desempenho produziu 34 itens diferentes, foi eficiente durante nove meses, com índice de eficiência de 96%, no ano de 2017. A combinação ou sequência entre os tipos de culturas, tamanho das áreas destinadas a cada uma e épocas de plantio, constituem uma dinâmica produtiva capaz de promover a eficiência de cada UP. A identificação das unidades eficientes e o entendimento da dinâmica e das boas práticas produtivas, pode auxiliar os agricultores com menor eficiência, na melhoria do desempenho.